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[4/6] Arm(R) Ethos(TM)-U NPU TIR to CS for Conv2D #8811

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244 changes: 244 additions & 0 deletions python/tvm/relay/backend/contrib/ethosu/tir_to_cs_translator.py
Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,8 @@
import ethosu.vela.api as vapi # type: ignore

import tvm
from tvm.tir import stmt_functor
from tvm.relay.backend.contrib.ethosu import util
from tvm.relay.backend.contrib.ethosu import vela_api
from tvm.relay.backend.contrib.ethosu.tir import spec

Expand All @@ -39,6 +41,14 @@ class BufferType(Enum):
output = auto()


_REGION_MAP = {
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for a follow-on: should this become enum.IntEnum?

BufferType.constant: 0,
BufferType.scratch: 1,
BufferType.input: 3,
BufferType.output: 4,
}


class BufferInfo(NamedTuple):
"""A data structure to hold metadata of the buffer"""

Expand All @@ -49,6 +59,72 @@ class BufferInfo(NamedTuple):
btype: BufferType


def translate(tir_module, params):
"""This will take an tir module for the NPU
and compile to command stream

Parameters
----------
tir_module : tvm.IRModule
The TIR module containing ethosu extern calls
params : dict
A dictionary containing TIR primfunc argument ordering
idx to constant NDArray map
accel_type : ethosu.vela.api.NpuAccelerator
the accelerator variant the tir module needs to compiled to

Returns
-------
cs : str
An hex string of the bytes of command stream
encoded_constants : str
An hex string of the bytes that includes concat'd
encoded weights, encoded biases and scales.
scratch_size : int
The size of the scratch buffer needed.
"""

buffer_info = extract_buffer_info(tir_module, params)
extern_calls = extract_extern_calls(tir_module)
_npu_ops = list()
for extern_call in extern_calls:
_npu_ops.append(translate_ethosu_tir_extern_call(extern_call))
_npu_ops, constant_tensor, scratch_size = assign_addresses(buffer_info, _npu_ops)
target_accel_type = vela_api.get_target_accel_type()
cmds = vapi.npu_generate_register_command_stream(_npu_ops, target_accel_type)
payload = vapi.npu_create_driver_payload(cmds, target_accel_type)
hex_value = "" if constant_tensor is None else constant_tensor.tobytes().hex()
return payload.hex(), hex_value, scratch_size


def extract_extern_calls(mod):
"""This function will obtain all extern
calls from a TIR module
Parameters
----------
mod : tvm.IRModule
The TIR Module for NPU

Returns
-------
list
of tvm.tir.Call objects
that are tir extern calls
"""
# There should only be a single function
assert len(mod.functions.items()) == 1
primfunc = mod.functions.items()[0][1]

extern_calls = list()

def populate_extern_calls(stmt):
if isinstance(stmt, tvm.tir.Call) and stmt.op.name == "tir.call_extern":
extern_calls.append(stmt)

stmt_functor.post_order_visit(primfunc.body, populate_extern_calls)
return extern_calls


def extract_buffer_info(mod, param_dict):
"""
This function is to read the tvm.IRModule that
Expand Down Expand Up @@ -101,6 +177,156 @@ def populate_allocate_buffer_info(stmt):
return buffer_info


def assign_addresses(buffer_info, npu_ops):
"""This function will assign addresses to tensors
within two buffers : scratch and constants.
The scratch is the buffer created to hold all intermediary data
The constants is the buffer created via unifying all the constant data
(post-encoding).
Parameters
----------
buffer_info : dict
This is the dictionary obtained via calling extract_buffer_info.
The key is the buffer name to BufferInfo
npu_ops : list
A list of Vela NpuOps with tir.Loads for addresses
Returns
-------
npu_ops : list
A list of Vela NpuOps with addesses within scratch and constant buffers
constant_tensor : NDArray
A unified constant data array of uint8 as the constant buffer
scratch_size : int
The size of the scratch tensor.
"""

def replace_npu_fm_with_address(npu_fm):
assert isinstance(npu_fm.tiles.addresses[0], tvm.tir.Load)
# We currently does not support tiles
# Change this when tiles are needed
# (i.e. when using rolling buffers)
assert npu_fm.tiles.addresses[1:] == [0, 0, 0]
npu_fm.tiles.addresses[1:] = [0, 0, 0]
buffer = npu_fm.tiles.addresses[0].buffer_var
assert buffer in buffer_addresses.keys()
address, buffer_type = buffer_addresses[buffer]
npu_fm.tiles.addresses[0] = address
npu_fm.region = _REGION_MAP[buffer_type]
return npu_fm

def replace_npu_address_range_with_address(npu_addr_range):
assert isinstance(npu_addr_range.address, tvm.tir.Load)
buffer = npu_addr_range.address.buffer_var
assert buffer in buffer_addresses.keys()
address, buffer_type = buffer_addresses[buffer]
return vapi.NpuAddressRange(_REGION_MAP[buffer_type], address, npu_addr_range.length)

def replace_tir_loads(npu_object):
if isinstance(npu_object, vapi.NpuFeatureMap):
return replace_npu_fm_with_address(npu_object)
if isinstance(npu_object, vapi.NpuAddressRange):
return replace_npu_address_range_with_address(npu_object)
return npu_object

def classify_io(buffer):
for _npu_op in npu_ops:
if issubclass(type(_npu_op), vapi.NpuBlockOperation):
if _npu_op.ifm and _npu_op.ifm.tiles.addresses[0].buffer_var == buffer:
return BufferType.input
if _npu_op.ifm2 and _npu_op.ifm2.tiles.addresses[0].buffer_var == buffer:
return BufferType.input
if _npu_op.ofm and _npu_op.ofm.tiles.addresses[0].buffer_var == buffer:
return BufferType.output

raise ValueError(f"Unused IO : {buffer} in tir module.")

scratch_size = 0
constant_tensor = None
buffer_addresses = dict()
for _buffer, info in buffer_info.items():
if info.values is not None:
assert np.dtype(info.dtype) == np.uint8
assert info.btype == BufferType.constant
assert len(info.shape) == 1
if constant_tensor is None:
buffer_addresses[_buffer] = (0, info.btype)
assert info.values.dtype == np.uint8
size_in_bytes = info.values.size
# Every memory address the NPU access have to be 16 byte aligned
size_in_bytes = util.round_up(size_in_bytes, 16)
constant_tensor = np.resize(info.values, size_in_bytes)
else:
buffer_addresses[_buffer] = (constant_tensor.size, info.btype)
assert info.values.dtype == np.uint8
size_in_bytes = info.values.size
# Every memory address the NPU access have to be 16 byte aligned
size_in_bytes = util.round_up(size_in_bytes, 16)
constant_tensor = np.append(constant_tensor, np.resize(info.values, size_in_bytes))
else:
size_in_bytes = int(
(np.iinfo(np.dtype(info.dtype)).bits // 8) * np.prod(list(info.shape))
)
# Every memory address the NPU access have to be 16 byte aligned
size_in_bytes = util.round_up(size_in_bytes, 16)
if info.btype == BufferType.input_or_output:
buffer_type = classify_io(_buffer)
assert buffer_type in (BufferType.input, BufferType.output)
address = 0
buffer_addresses[_buffer] = (address, buffer_type)
else:
assert info.btype == BufferType.scratch
address = scratch_size
scratch_size += size_in_bytes
buffer_addresses[_buffer] = (address, info.btype)

for npu_op in npu_ops:
for attr_name, attr in npu_op.__dict__.items():
if isinstance(attr, list):
new_attr = list()
for attr_ in attr:
new_attr.append(replace_tir_loads(attr_))
setattr(npu_op, attr_name, new_attr)
else:
setattr(npu_op, attr_name, replace_tir_loads(attr))

return npu_ops, constant_tensor, scratch_size


def translate_ethosu_tir_extern_call(tir_extern_call):
"""This is a dispatcher function to dispatch
correct translation call depending on the extern call's
first argument"""
supported_extern_calls = {
"ethosu_conv2d": translate_ethosu_conv2d,
"ethosu_copy": translate_ethosu_copy,
}
ext_call_type = tir_extern_call.args[0].value
assert ext_call_type in supported_extern_calls.keys(), f"{ext_call_type} is not yet supported"
npu_op = supported_extern_calls[ext_call_type](tir_extern_call)
# Some conversions return additional outputs
# if they are needed, the caller should use the function directly
if isinstance(npu_op, tuple):
return npu_op[0]
return npu_op


def translate_ethosu_copy(tir_extern_call):
"""This function will translate a tir ethosu_copy extern_call
as produced by Relay to TIR compilation.
Parameters
----------
tir_extern_call : tvm.tir.Call

Returns
-------
ethosu.vela.api.NpuDmaOperation
The vela object containing the params of ethosu_copy
"""
# We skip the first element as it is the extern_call function name
serial_object = spec.create_serial_object(spec.SerialCopy, tir_extern_call.args[1:])
return _create_npu_dma_op(serial_object)


def _convert_clip_bounds(npu_op):
"""
This function will convert the min and max value
Expand Down Expand Up @@ -330,3 +556,21 @@ def _create_npu_resampling_mode(
mode = str(mode.value)
assert mode in mode_map.keys()
return mode_map[mode]


def _create_npu_dma_op(serial_copy):
"""This is a helper function to capture the list of arguments
to create a NpuDmaOperation object"""
src = vapi.NpuAddressRange(
# region will be updated later
region=0,
address=serial_copy.read_address,
length=int(serial_copy.length.value),
)
dest = vapi.NpuAddressRange(
# region will be updated later
region=0,
address=serial_copy.write_address,
length=int(serial_copy.length.value),
)
return vapi.NpuDmaOperation(src, dest)
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